A Case Study on Probabilistic Technico-Economic Analysis Including Maintenance Cost for Hydroelectric Turbine Fatigue Risk

Abstract

AbstractThis paper presents a novel approach for planning replacement projects using prognostic developed for turbines and generators to try to defer unit replacements by maximizing economic gains while minimizing risk. In the same analysis in which we optimize replacement dates, we would like to also optimize operation and maintenance plans since each turbine design is affected differently by these plans. The current maintenance plans scheduled at fixed intervals and the unit commitment strategy solely based on hydraulic efficiency are therefore also questioned. The goal of this analysis is to demonstrate that maintenance and operating plans need to be adjusted to minimize the probability of regret when optimizing NPV (Net Present Value) by changing replacement dates while considering equipment prognostic. For this study, the impact of inspections, frequency of unit start-up and deferred equipment replacement have been evaluated by comparing them to a reference scenario where the equipment would have been operated under traditional frameworks. The analysis demonstrated the following points: It is possible to observe the impacts of the improvements (frequency of inspection, start-up, replacement date, etc.) separately in the technico-economic analyses; Unexpected breakdowns can be taken into account for informed risk management; Investment deferrals can be analyzed by taking into account the risk; Maintenance and repair can be rigorously taken into account by the model. In fact, the proposed model allows to define the required maintenance and operation plans according to the replacement strategy that will be chosen in a global optimization of the unit fleet. The sensitivity analysis presented shows the importance of adjusting operation and maintenance according to the specific design of each runner and the importance of the chosen deferral date. With this kind of analysis, the decision-maker could possibly (while controlling the risk): Distribute the number of start-ups or other damaging conditions differently in order to protect some units while maximizing the use and wear of others; Postpone as much as possible the replacement of those equipments that show very little risk of failure. The paper will be structured as follows. First, an overview of the modelling strategy will be presented. Then, the parameters of the case study and the methodology will be detailed. A sensitivity analysis will show the impacts of the different assumptions on the mean net present value and the probability of regret. Finally, we will discuss the results for several units in terms of applicability for decision making and asset management.KeywordsHydroelectric turbinesAsset managementReliabilityMonte-Carlo simulationNet Present ValueOptimal operation and maintenanceAnticipated turbine replacement